CN111462501B - Super-view area passing system based on 5G network and implementation method thereof - Google Patents
Super-view area passing system based on 5G network and implementation method thereof Download PDFInfo
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- CN111462501B CN111462501B CN202010435795.4A CN202010435795A CN111462501B CN 111462501 B CN111462501 B CN 111462501B CN 202010435795 A CN202010435795 A CN 202010435795A CN 111462501 B CN111462501 B CN 111462501B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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Abstract
The utility model discloses a super-vision zone passing system based on 5G network and an implementation method thereof, comprising the following steps: the central server is connected with the plurality of perception sensors, each perception sensor is arranged at an intersection, and the central server receives real-time traffic image data collected by the network camera; the central server stores the real-time traffic image data and sends the real-time traffic image data to a pedestrian mobile terminal and/or a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna connected with a transmitter. Road participants (drivers and pedestrians) realize transparent and super-view area observation by means of a 5G network technology, and realize effective control of driving behaviors and avoidance of occurrence probability of traffic accidents. Greatly protecting the safety of the life and property of the passerby.
Description
Technical Field
The invention relates to a super-view area passing system based on a 5G network and an implementation method thereof.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
The number of people died in the whole country due to traffic accidents exceeds 10-26 ten thousand per year, and the number of people died of ten thousand vehicles is 13.7. 10 times higher than in japan. The death worldwide exceeds 50-125 million each year. The cumulative number of deaths exceeds 3000 ten thousand. 3000 million people are injured due to traffic accidents every year around the world, and 300 million people are permanently disabled. Economic losses caused by traffic accidents reach trillion every year, and casualties occur frequently due to the traffic accidents.
The main reasons for high incidence of traffic accidents are: there are blind areas: traffic topics-participants (drivers, pedestrians) observe roads and other traffic participants for the existence of blind areas; a secondary reason is that obstacles obstruct the driver's view and are unable to find the opponent of the impending traffic accident. In the prior art, blind areas and beyond-view areas of road passers cannot be eliminated.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a super-view area passing system based on a 5G network and an implementation method thereof, road participants (drivers and pedestrians) realize mutual transparent super-view area observation by means of a 5G network technology, and realize effective control of driving behaviors and avoidance of traffic accidents. Greatly protecting the safety of the life and property of the passerby.
In a first aspect, the present disclosure provides a beyond visual area passing system based on a 5G network;
a super-view area passing system based on a 5G network comprises: the central server is connected with the plurality of perception sensors, each perception sensor is arranged at an intersection, and the central server receives real-time traffic image data collected by the network camera; the central server stores the real-time traffic image data and sends the real-time traffic image data to a pedestrian mobile terminal and/or a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna connected with a transmitter.
In a second aspect, the present disclosure provides an implementation method of a super-view area passing system based on a 5G network;
an implementation method of a super-view area passing system based on a 5G network comprises the following steps:
the method comprises the steps that a central server receives real-time traffic image data collected by a perception sensor of an intersection; the central server stores the real-time traffic image data and sends the real-time traffic image data to the pedestrian mobile terminal and the vehicle-mounted terminal of the motor vehicle through the 5G transmitting antenna connected with the transmitter.
Compared with the prior art, the beneficial effect of this disclosure is:
because the 5G network is adopted, the problem of slow data transmission is solved, pedestrians and drivers at the intersection can check traffic conditions in real time through the terminal carried by the pedestrians and the drivers, and the passing through area of the intersection can be realized.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
Fig. 1 is a schematic system architecture diagram according to a first embodiment of the disclosure;
fig. 2 is a plan view of an intersection system according to a first embodiment of the present disclosure;
FIG. 3 is a schematic view of an intersection building or tree blocking a driver according to a first embodiment of the disclosure;
FIG. 4 is a schematic view of a blind area of a car according to a first embodiment of the disclosure;
FIG. 5 is a schematic view of a blind area of a passenger car according to a first embodiment of the disclosure;
FIG. 6 is a graph illustrating a relationship between a driving safety distance and a driving speed of an automobile according to a first embodiment of the present disclosure;
FIG. 7 is a schematic view illustrating an overlap of dangerous driving zones of a vehicle according to a first embodiment of the present disclosure;
fig. 8 is a schematic diagram illustrating a danger area generated by all vehicles participating in traffic according to the first embodiment of the present disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In the present embodiment of the disclosure, "and/or" is only one kind of association relation describing an association object, and means that there may be three kinds of relations. For example, a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the present application, "a plurality" means two or more than two.
5G technology, i.e. 5 th generation communication technology: the method is characterized in that the information transmission rate is high in three aspects (1), the information transmission rate is more than 100 times of that of 4G communication, the mobile transmission can reach 1GBPS, the real-time performance is good, and the large-capacity requirements of information acquisition, processing and exchange of road conditions and the motion states of road participants can be met; (2) the delay is short, the real-time control is suitable, and the real-time dynamic processing requirements of roads, vehicles and pedestrians can be met; (3) the interactivity is good, and the information can be conveniently exchanged in real time.
The road information is collected by the network camera and then transmitted to the central server, the central server completes the storage, processing and forwarding of the road information, and the transmitter completes the transmission of the road information. The driver or road traveler receives the road information from the system via the terminal, the terminal predicts the position, motion state and road information dynamically based on the road information, and the terminal displays road state, especially blind area state, and displays and prompts possible collision.
The high-definition network camera captures real-time information of road conditions, vehicles and pedestrians, the single-mode optical fiber is used for transmitting the road condition information, the network interface receives the information transmitted by the optical fiber, and the central server receives the road condition information transmitted by the optical fiber. And storing and backing up the information, and processing the information by the central server. The processed information is sent to an interface, an optical fiber is connected, the information is sent to a transmitter by the optical fiber, and the transmitter performs multi-stage amplification on the information and sends the information to a 5G standard transmitting antenna. The antenna changes the road condition information into a 5G electromagnetic wave mode to be transmitted, and the vehicle-mounted intelligent terminal or the non-motorized pedestrian mobile phone terminal receives the 5G road condition information to obtain and display comprehensive road condition information.
The embodiment one, this embodiment provides a beyond visual area passing system based on 5G network;
as shown in fig. 1, a super view area passing system based on a 5G network includes: the central server is connected with a plurality of perception sensors, and each perception sensor is arranged at an intersection as shown in figure 2; the central server receives real-time traffic image data acquired by the network camera; the central server stores the real-time traffic image data and sends the real-time traffic image data to a pedestrian mobile terminal and/or a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna connected with a transmitter.
The super-vision area refers to the area beyond the visual field range of the traffic participants.
Furthermore, the pedestrian mobile terminal and/or the motor vehicle-mounted terminal collects the own mobile data and uploads the mobile data to the transmitter through the 5G transmitting antenna, the transmitter uploads the collected mobile data of the mobile terminal and/or the motor vehicle-mounted terminal to the central server, and the central server integrates the real-time traffic image data and the mobile data and then distributes the data to the pedestrian mobile terminal and/or the motor vehicle-mounted terminal.
It should be understood that the vehicle-mounted terminal of the motor vehicle collects the movement data of the vehicle, and the movement data comprises one or more of the following data: the current position of the motor vehicle, the current driving route of the motor vehicle, the current driving speed of the motor vehicle, the current vehicle type, the current cargo capacity of the motor vehicle, the current number of people carrying the motor vehicle, the current vehicle condition or the current road condition within the set range of the motor vehicle.
Further, the system further comprises:
calculating a safety range for each traffic participant, wherein the traffic participants refer to pedestrians or vehicles; when the safety range of one traffic participant is overlapped with the safety ranges of other traffic participants, an alarm prompt is sent out, the ratio of the overlapped area to the safety range of each traffic participant is further calculated, when the ratio exceeds a set threshold value, a serious alarm is sent out to the two traffic participants in the overlapped area, and an alarm prompt is also sent out to the traffic participants in a set distance range outside the overlapped area.
Furthermore, the central server is connected with each perception sensor through an optical fiber.
It should be understood that the perception sensor includes one or more of the following forms: radar, sonar, speedometer or camera.
Further, the central server is connected with the transmitter through an optical fiber.
Furthermore, the camera is used for capturing road all-dimensional road condition information, vehicle information, pedestrian information and shelter information and uploading the information to the central server.
Further, the mobile terminal and the vehicle-mounted terminal receive road information issued by the central server, and the road information displays the road position, the motion state and the potential dangerous event where the current mobile terminal or the vehicle-mounted terminal is located.
Further, the transmitter is used for carrying out signal amplitude amplification and signal power amplification on the information of the central server, and then sending the information to a pedestrian mobile terminal and a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna.
The second embodiment provides an implementation method of a super-view area passing system based on a 5G network;
an implementation method of a super-view area passing system based on a 5G network comprises the following steps:
the method comprises the steps that a central server receives real-time traffic image data collected by a perception sensor of an intersection; the central server stores the real-time traffic image data and sends the real-time traffic image data to the pedestrian mobile terminal and the vehicle-mounted terminal of the motor vehicle through the 5G transmitting antenna connected with the transmitter.
As one or more embodiments, the implementation method further includes:
the pedestrian mobile terminal and/or the motor vehicle-mounted terminal collects the mobile data of the pedestrian and/or the motor vehicle-mounted terminal, the mobile data is uploaded to the transmitter through the 5G transmitting antenna, the transmitter uploads the collected mobile data of the mobile terminal and/or the motor vehicle-mounted terminal to the central server, and the central server integrates the real-time traffic image data and the mobile data and then distributes the data to the pedestrian mobile terminal and/or the motor vehicle-mounted terminal.
As one or more embodiments, the implementation method further includes:
calculating a safety range for each traffic participant, wherein the traffic participants refer to pedestrians or vehicles;
when the safety range of one traffic participant is overlapped with the safety ranges of other traffic participants, an alarm prompt is sent out, the ratio of the overlapped area to the safety range of each traffic participant is further calculated, when the ratio exceeds a set threshold value, a serious alarm is sent out to the two traffic participants in the overlapped area, and an alarm prompt is also sent out to the traffic participants in a set distance range outside the overlapped area.
Further, the consideration factor of the safety range is calculated through a pre-trained deep learning model.
Further, the training step of the pre-trained deep learning model comprises:
constructing a convolutional neural network model;
constructing a training set, wherein the training set comprises: the vehicle type, the cargo capacity and the current vehicle speed of the traffic participants with known safety ranges;
and inputting the training set into the convolutional neural network model for training, stopping training when the loss function reaches the minimum value, and outputting the trained convolutional neural network model.
The reaction time of the driver is generally: 0.4-1.0 seconds, fast reacting drivers are: 0.4-0.6 second, when the car runs at 50KM/S, the driver can make emergency response after the car runs for 6-7 meters.
Vehicle brake actuation response time: 0.15-0.3 second, the vehicle advances 2-4 meters; if the automobile runs at 50 kilometers per hour, the automobile runs for 13.8 meters within 1 second, and the common braking distance is 7-13 meters. Then the car realizes that the car is completely stopped from the driver's emergency brake, and the car has traveled 20-30 meters.
If the automobile runs at 100 kilometers per hour within 1 second, the automobile runs for 28 meters, and the common braking distance is 40-50 meters. The car realizes from the driver that the car is completely stopped by generating an emergency brake, and the car has traveled 78 meters.
On the expressway, the vehicle travels at 120 km/h, and the vehicle has traveled a distance of 100 m, recognizing that the vehicle is completely stopped from the driver's emergency brake.
As shown in fig. 6, the safe distance traveled by the vehicle is related to the speed:
when the automobile runs at high speed, namely the speed is more than 100km/h, the safe distance is more than 100 meters.
When the automobile runs fast, namely the speed is more than 60km/h, the safe distance is more than 60 meters; for example, when the vehicle speed is 80km/h, the safe vehicle distance is more than 80 meters.
When the automobile runs at a medium speed, namely the speed is about 50km/h, the safe distance is not less than 50 meters.
When the automobile runs at low speed, namely the speed of the automobile is below 40km/h, the safe distance is not less than 30 meters.
When the automobile runs at a slow speed, namely the speed of the automobile is below 20km/h, the safe distance is not less than 10 meters.
Traffic accidents: the time-space conflict is generated by two or more objects with independent time-space occupation characteristics, and the objects are damaged or disintegrated. This process is referred to as a traffic accident, and may also be referred to as a space-time preemption event.
Prevention mode: first, the main body, the time and the place of the conflict are searched for when the time and space fierce competition occurs. In advance, the event participants are intervened, the contradictions are resolved, and traffic accidents are avoided.
Subject information of traffic participation: vehicles and pedestrians participating in traffic are perceived. The system comprises an internet of things system, a mobile communication system, a traffic snapshot system, a public security sky-eye system and a satellite system. After information integration, all vehicle quantities participating in traffic and positions, moving speeds and safety ranges of pedestrians can be obtained. At present, the information is only used for solving a case and restoring traffic accidents. The information can play a larger role, a larger network is compiled, and the task of protecting people from going out safely is completed.
The super-view area passing system comprises: from hardware branch, sensor system that the network uploaded: the middle-end machine worn by the vehicles participating in the traffic transmits the information of the vehicles, such as position, driving route, driving speed, vehicle type, cargo carrying, manned, vehicle condition, road condition and the like. And receiving various instructions, road conditions and traffic service information sent by the system. The road sets up perception sensors such as various radars, sonar, tachymeter, the camera that detect the vehicle and constitutes perception net, public perception net: mobile communication network, satellite optical and infrared capturing network.
The software is divided into: a system operation platform and a terminal installation operation part; the whole, system and complex functions are completed in the system. Terminal portion: the vehicle-related tasks such as acquiring information reception of other traffic participants who may have traffic accidents with the vehicle, processing the information, and then providing the information to the driver of the vehicle in the form of screen, voice, light, and the like are completed. Emergency treatment preparation and corresponding avoidance treatment are carried out for avoiding possible traffic accidents.
And (3) processing algorithm: the ant movement overlapping space-time algorithm is characterized in that each traffic participant is equivalent to one ant in a large number of traffic participants, has a position and a movement speed, and has the randomness of changing lanes. The safety range of each traffic participant is calculated based on the vehicle information (vehicle type, load carrying vehicle, vehicle speed), and if each traffic participant overlaps with the safety ranges of other vehicles, the possibility of traffic accidents and collisions may occur. As shown in fig. 7, the roots of the danger zones overlap, and the probability of a traffic collision is 100%. And according to the delay result, the system sends the information of the dangerous area to the terminal vehicle in time.
The terminal vehicle receives the information of the danger areas, delays whether the danger areas of the vehicle and other vehicles are overlapped, provides a vehicle avoiding mode and reduces the possibility of overlapping of the danger areas. Traffic accident sounding is avoided.
A vehicle is a danger area, a moving danger area. When the pedestrian enters the dangerous area, traffic accidents may occur. When a vehicle enters a dangerous area of the vehicle, traffic accidents such as collision, rear-end collision and the like can occur.
Intervention measures are as follows: the dangerous areas that pedestrians and electric vehicles enter the automobile are reduced. The speed of the automobile is prompted, and the danger area can be reduced.
And reminding the vehicles running in the crossing, wherein at the moment, because the vision is blocked by the crossing and the barrier, the beyond-the-sight-zone system is required to provide service, and the information of the vehicles on the crossing road and whether the dangerous zones are overlapped or not can be known in time.
As shown in fig. 8, at the intersection controlled by the traffic lights, the traffic lights of vehicles and pedestrians are used for alternately passing, and the safe driving is guaranteed. When no traffic light is provided or traffic lights are provided, individual vehicles run the red light or pedestrians run the red light, the traffic accident is very easy to cause. Particularly, a tractor, a bull and a man are drawn out from the country lane from time to time. The probability of traffic accidents is very high. The blind area of the vehicle is shown in fig. 3, 4 and 5, the reaction time of the driver of the vehicle, and the reaction time of the driver of the vehicle.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (8)
1. A super-view area passing system based on a 5G network is characterized by comprising: the central server is connected with the plurality of perception sensors, each perception sensor is arranged at an intersection, and the central server receives real-time traffic image data collected by the network camera; the central server stores the real-time traffic image data and sends the real-time traffic image data to a pedestrian mobile terminal and/or a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna connected with a transmitter; the terminal receives the road information transmitted by the system, dynamically predicts the position, the motion state and the road information of the terminal according to the road information, displays the road conditions including blind area conditions and displays and prompts possible collision;
calculating a safety range for each traffic participant, wherein the traffic participants refer to pedestrians or vehicles; when the safety range of one traffic participant is overlapped with the safety ranges of other traffic participants, an alarm prompt is sent out, the ratio of the overlapped area to the safety range of each traffic participant is further calculated, when the ratio exceeds a set threshold value, a serious alarm is sent out to the two traffic participants in the overlapped area, and an alarm prompt is also sent out to the traffic participants in a set distance range outside the overlapped area.
2. The system according to claim 1, wherein the pedestrian mobile terminal and/or the vehicle-mounted terminal of the vehicle collects the own mobile data and uploads the mobile data to the transmitter through the 5G transmitting antenna, the transmitter uploads the collected mobile data of the mobile terminal and/or the vehicle-mounted terminal of the vehicle to the central server, and the central server integrates the real-time traffic image data and the mobile data and then distributes the data to the pedestrian mobile terminal and/or the vehicle-mounted terminal of the vehicle.
3. The system of claim 1, wherein the vehicle terminal of the vehicle collects movement data of the vehicle, the movement data comprising one or more of the following data: the current position of the motor vehicle, the current driving route of the motor vehicle, the current driving speed of the motor vehicle, the current vehicle type, the current cargo capacity of the motor vehicle, the current number of people carrying the motor vehicle, the current vehicle condition or the current road condition within the set range of the motor vehicle.
4. The system of claim 1, wherein the central server is connected to each of the plurality of perception sensors by an optical fiber; the central server is connected with the transmitter through an optical fiber;
the mobile terminal and the vehicle-mounted terminal receive road information issued by a central server, and the road information displays the road position, the motion state and the potential dangerous event where the current mobile terminal or the vehicle-mounted terminal is located;
and the transmitter is used for amplifying the signal amplitude and the signal power of the information of the central server and then transmitting the information to a pedestrian mobile terminal and a vehicle-mounted terminal of a motor vehicle through a 5G transmitting antenna.
5. An implementation method of a super-view area passing system based on a 5G network is characterized by comprising the following steps:
the method comprises the steps that a central server receives real-time traffic image data collected by a perception sensor of an intersection; the central server stores the real-time traffic image data and sends the real-time traffic image data to the pedestrian mobile terminal and the vehicle-mounted terminal of the motor vehicle through a 5G transmitting antenna connected with the transmitter; the terminal receives the road information transmitted by the system, dynamically predicts the position, the motion state and the road information of the terminal according to the road information, displays the road conditions including blind area conditions and displays and prompts possible collision;
calculating a safety range for each traffic participant, wherein the traffic participants refer to pedestrians or vehicles; when the safety range of one traffic participant is overlapped with the safety ranges of other traffic participants, an alarm prompt is sent out, the ratio of the overlapped area to the safety range of each traffic participant is further calculated, when the ratio exceeds a set threshold value, a serious alarm is sent out to the two traffic participants in the overlapped area, and an alarm prompt is also sent out to the traffic participants in a set distance range outside the overlapped area.
6. The method of claim 5, further comprising:
the pedestrian mobile terminal and/or the motor vehicle-mounted terminal collects the mobile data of the pedestrian and/or the motor vehicle-mounted terminal, the mobile data is uploaded to the transmitter through the 5G transmitting antenna, the transmitter uploads the collected mobile data of the mobile terminal and/or the motor vehicle-mounted terminal to the central server, and the central server integrates the real-time traffic image data and the mobile data and then distributes the data to the pedestrian mobile terminal and/or the motor vehicle-mounted terminal.
7. The implementation of claim 6 wherein the safety margin considerations are calculated by a pre-trained deep learning model.
8. The method of claim 7, wherein the step of training the pre-trained deep learning model comprises:
constructing a convolutional neural network model;
constructing a training set, wherein the training set comprises: the vehicle type, the cargo capacity and the current vehicle speed of the traffic participants with known safety ranges;
and inputting the training set into the convolutional neural network model for training, stopping training when the loss function reaches the minimum value, and outputting the trained convolutional neural network model.
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